Product updates
Public beta opens March 24
Sean Looper
February 13, 2026
•
5 min read
For years, delivering 3D content has always meant a tradeoff. To achieve reach, you sacrifice fidelity for scale. If you need that content delivered with high quality, you pay per-user premiums and limit reach to a select few markets. There hasn't been a way to get both.
We built Miris to eliminate those tradeoffs. On March 24, we're opening the public beta to our platform so developers can see the difference for themselves.
Sharing 3D assets at scale is a delivery challenge, one that has been stuck between two imperfect approaches.
Client-side rendering with formats like glTF puts the user in control. Assets download directly to the device and render locally, which means zero server dependency and true offline access. For simple models, this works well. But high-fidelity assets create massive file sizes, long load times, and device compatibility headaches. A detailed product model or architectural visualization can easily exceed what's practical for mobile browsers.
Pixel streaming takes a different path, and gets different things right. By rendering on remote high-end GPUs and streaming video to the client, it delivers full visual fidelity regardless of the end device. No download, no local hardware constraints. The tradeoff is latency, expensive edge-GPU infrastructure, and a scaling ceiling that typically tops out at dozens or hundreds of concurrent users.
Both approaches have real merit. But developers today are forced to choose between them, trading speed for fidelity, or fidelity for reach. What's been missing is a way to deliver fast, high-fidelity 3D that scales across devices at billion-user scale, without the infrastructure costs that make it impractical.
Miris takes a fundamentally different approach. Instead of compressing assets for client-side download or provisioning GPU infrastructure for pixel streaming, Miris operates as a managed streaming service. You upload your asset as an OpenUSD file, an open scene description format with native support in most professional 3D tools (Blender, Maya, Houdini, Unreal, and others). Miris handles the rest, transforming it into a streamable, high-fidelity 3D experience that loads in sub-second time on any device. The economics look closer to that of streaming video than cloud rental.
With a sub-second time-to-interaction, users can see and interact with high-fidelity 3D content almost immediately, regardless of total asset complexity. A 500MB asset loads and responds as quickly as a simple 5MB glTF.
Because Miris streams spatial data rather than rendered frames, you don't need edge GPUs for every concurrent user. The architecture scales without the infrastructure costs that make pixel streaming prohibitive at volume.
This means:
Starting today, developers can get in the queue for our public beta, which opens on March 24. We’ll be opening the beta in waves, so make sure you lock in your spot!
When the beta opens, you'll have immediate access to sample assets so you can see Miris in action before uploading your own content. Developer documentation will walk you through integration, and the entire flow is self-serve—no sales calls required to get started.
We're onboarding beta users in waves to ensure quality support, but our target is simple: we want developers to go from signup to streaming their own 3D asset within a week. That's enough time to validate whether Miris solves your delivery problems.
If you're building web experiences that require 3D (product configurators, architectural visualization, digital twins, interactive retail) and you've been fighting the tradeoffs of current delivery methods, we'd like to show you a better approach.
Sign up for the free public beta here so you’re locked in for March 24th. We're building this with you, and early feedback shapes what we ship.
Questions? We’d love to hear from you.
Streaming video reshaped media consumption; we're doing the same for 3D. Join a small team solving tough spatial streaming, content delivery, and developer experience challenges.
Technical deep-dives on adaptive spatial streaming, the infrastructure challenges of 3D at scale, and what we're learning as we build. Written by the team doing the work.
